Towards data-driven tele-medicine intelligence: community-based mental healthcare paradigm shift for smart aging amid COVID-19 pandemic

Cheng, Lan; Chan, Wai-Kin; Peng, Yi; Qin, Harry

doi:10.1007/s13755-022-00198-4

Cited by 8 publications

(3 citation statements)

References 26 publications

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“…Future research in this domain could explore the refinement and development of predictive models, with a particular focus on incorporating real-time data sources and advanced machine learning techniques [30,31]. Investigating the integration of predictive models with smart city infrastructure, such as intelligent traffic management systems, could enhance the practical application of these models.…”

Section: Discussionmentioning

confidence: 99%

Towards Green Innovation in Smart Cities: Leveraging Traffic Flow Prediction with Machine Learning Algorithms for Sustainable Transportation Systems

Tao,

Cheng,

Zhang

et al. 2023

Sustainability

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The emergence of smart cities has presented the prospect of transforming urban transportation systems into more sustainable and environmentally friendly entities. A pivotal facet of achieving this transformation lies in the efficient management of traffic flow. This paper explores the utilization of machine learning techniques for predicting traffic flow and its application in supporting sustainable transportation management strategies in smart cities based on data from the TRAFFIC CENSUS of the Hong Kong Transport Department. By analyzing anticipated traffic conditions, the government can implement proactive measures to alleviate congestion, reduce fuel consumption, minimize emissions, and ultimately improve quality of life for urban residents. This study proposes a way to develop traffic flow prediction methods with different methodologies in machine learning with a comparison with other results. This research aims to highlight the importance of leveraging machine learning technology in traffic flow prediction and its potential impact on sustainable transportation systems for the green innovation paradigm. The findings of this research have practical implications for transportation planners, policymakers, and urban designers. The predictive models demonstrated can support decision-making processes, enabling proactive measures to optimize traffic flow, reduce emissions, and improve the overall sustainability of transportation systems.

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Section: Discussionmentioning

confidence: 99%

Towards Green Innovation in Smart Cities: Leveraging Traffic Flow Prediction with Machine Learning Algorithms for Sustainable Transportation Systems

Tao,

Cheng,

Zhang

et al. 2023

Sustainability

Self Cite

View full text Add to dashboard Cite

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“…and recovery [7], effectively overcoming challenges such as extended wait times, geographical distance, and health care personnel shortages, particularly in remote areas. The wide adoption of telemedicine could benefit all stakeholders, such as patients, health care providers, health care institutions, and governments, especially after the COVID-19 pandemic, as evidenced by previous studies [8][9][10].…”

Section: Introductionmentioning

confidence: 87%

Assessing the Impact of Telemedicine Interventions on Health Care Costs and Utilization: A Scoping Review (Preprint)

Liu,

Kumluang,

Gaewkhiew

et al. 2024

Preprint

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BACKGROUND The utilization of telemedicine has increased notably since the onset of the pandemic. Understanding the influence of telemedicine on health care costs and utilization can contribute to the monitoring and evaluation of telemedicine programs. OBJECTIVE This scoping review aimed to document the potential impact of telemedicine on health care costs and utilization across diverse health care contexts and to offer a summary of the statistical methodological approaches employed in assessing the impact of telemedicine on health care costs and utilization. METHODS A literature search was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Extension for Scoping Reviews guidelines, spanning the last 10 years across 3 electronic databases: PubMed/Medline, Web of Science, and Scopus. The search strategy was in accordance with the PICO criteria; patients were defined as the target population; telehealth or telemedicine was defined as the intervention; and standard care or before-and-after self-comparison was defined as the comparison, with health care costs and utilization as the outcome measures. Additionally, the six different structural layers of the TOAST framework for telehealth services were utilized to characterize the interventions. The findings were synthesized and are presented in tables and figures for clarity. RESULTS Out of a total of 4,454 identified articles, 14 were selected for review, with approximately 36% (n=5) focusing on chronic conditions. The delivery modalities included telephone call, videoconference, web portal, and smartphone applications, mainly spanning teleconsultation, telemonitoring, and teletherapy with clinicians and nursing support or health care team involvement. Approximately 86% of the studies employed standard face-to-face clinical visits for the control group. Six out of the 12 studies evaluating health care costs and four out of the seven studies assessing health care utilization revealed statistically significant improvements in telehealth compared to the control group. In addition, approximately 43% of the studies conducted univariate and multivariable analyses, with half of the studies incorporating adjusted analyses to control for confounding variables. CONCLUSIONS Our scoping review suggested that, in the treatment phase, compared with standard face-to-face clinical visits, telemedicine has the potential to decrease health care costs and optimally utilize health resources. Additionally, a regression model was the most commonly used statistical approach for assessing the impact of telemedicine.

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“…This was done to close the service gap between the supply and demand sides of telehealth, investigate the proofbased method to combine care, address difficulties with aged policies, and lay the groundwork for the development of data-driven and community-based telemedicine. To establish Evidence-Based Medicine (EBM), Cheng [34] investigated the mechanisms of psychological disease preparedness, involving the collection, integration, and synergy of health parameters linking the three health service pipelines of response, intervention, and social variables.…”

Section: Related Workmentioning

confidence: 99%

Systematic literature review of healthcare services for the elderly: trends, challenges, and application scenarios

Guo,

Shukor,

Ishak

2023

IJPHS

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In recent years, healthcare for the elderly has received attention from researchers worldwide in the context of global aging. This paper provides a comprehensive overview of healthcare services for older people from 2019 to 2023, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to screen published papers in the Web of Science database, and identifies three different application scenarios for healthcare services for older people after analyzing the research objectives of the selected papers. This study examined the common health problems and needs of older adults, and the key parameters used to assess healthcare services for this population. This review also explores how healthcare providers can promote healthy aging and prevent age-related diseases in older patients. This study further evaluates the background and application areas of the papers and explains the methodology of the main ideas proposed in the studies. The review concludes with an analysis of the main trends and challenges that are likely to emerge in healthcare services for older people.

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Towards data-driven tele-medicine intelligence: community-based mental healthcare paradigm shift for smart aging amid COVID-19 pandemic

Cited by 8 publications

References 26 publications

Towards Green Innovation in Smart Cities: Leveraging Traffic Flow Prediction with Machine Learning Algorithms for Sustainable Transportation Systems

Towards Green Innovation in Smart Cities: Leveraging Traffic Flow Prediction with Machine Learning Algorithms for Sustainable Transportation Systems

Assessing the Impact of Telemedicine Interventions on Health Care Costs and Utilization: A Scoping Review (Preprint)

Systematic literature review of healthcare services for the elderly: trends, challenges, and application scenarios

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